Yuan An

I earned a Ph.D. degree in the Department of Computer Science at the University of Toronto. I received my M.CS. degree from the Faculty of Computer Science at Dalhousie University in Canada. I also earned my M.Eng. degree in Systems Engineering from the Department of Automation at Tsinghua University and my B.Eng. degree in Industrial Instruments and Automatic Detection from the Department of Automation at Tsinghua University, Beijing, China, as well.

My Corner
  • The Elements of Style by W. Strunk, Jr., my favorite book.
  • My blog on www.blogger.com. Unfortunately, it is not regularly bolgged.
  • I like Canadian by Erinest Miller Hemingway, read it Here.
  • As I read the article "How to do research at the MIT AI Lab" written by a bunch of MIT students, I found that the most useful and helpful part is section 12 "Emotional factors". As it says, the most important issue in doing research is to overcome the emotional failure and to recognize your personal success. Here is something from the article: "A recent survey of a group of Noble Laureates in science asked about the issue of self-doubt: had it been clear all along to these scientists that their work was earth-shattering? The unanimous response (out of something like 50 people) was that these people were constantly doubting the value, or correctness, of their work, and they went through periods of feeling that what they were doing was IRRELEVANT, OBVIOUS, or WRONG. A common and important part of any scientific progress is constant critical evaluation, and is some amount of UNCERTAINTY over the value of the work is an inevitable part of the PROGRESS."
  • What is the real value of studying in computer science? An article of NYT on Aug. 23, 2005, "A Techie, Absolutely, and More", referring to Prof. Lazowska of University of Washington says, it is less in acquiring a skill with technology tools - the usual definition of computer literacy - than in teaching students to manage complexity; to navigate and assess information; to master modeling and abstraction; and to think analytically in terms of algorithms, or step-by-step procedures.
  • Seven liberal arts: geometry, arithmetic, rhetoric, logic, grammar, music, and astronomy. The four cardinal virtues - fortitude, prudence, temperance, and justice.
  • What are numbers anyway? Are they a mere human construct or do they have some kind of objective existence? Was 1+1=2 true before there were people on the planet to assert it? Of course, these are glory of Creator. These issues have been debated centuries. The doctrine that abstract objects (like number and sets of numbers) have an objective existence with properties that people can only discover, not invent, is generally ascribed to Plato and, therefore, is called Platonism. Godel was adherent to this doctrine.
  • Inaccuracy, ambiguity, and diffuseness are the intrinsic nature of human languages. Machinery employing logic symbolism inherently excludes uncertainty. That's why these names, Gottlob Frege, Kurt Gödel, Alfred North Whitehead, Ludwig Wittgenstein, Bertrand Russell are so bright in representing human thought in symbolic structures. In the words of Bertrand Russell, "Because language is misleading, as well as because it is diffuse and inexact when applied to logic (for which it was never intended), logical symbolism is absolutely necessary to any exact or thorough treatment of mathematical philosophy." However, Gödel's incompleteness makes us to be lost in the jungle of Turing Machines, we are now in the middle of nowhere in speaking of 'computation'. The ill-fated AI has not been able to reconcile itself with the lugubrious outcome. Are we envisioning another Tower of Babel by the Semantic Web?
  • Gregory J Chaitin. Computers, paradoxes and the foundations of mathematics. American Scientist.
  • "There is little wonder why the systems we have been implementing for the last 50 years (i.e., the entire history of data processing) are so inflexible, unadaptable, misaligned, disintegrated, unresponsive, expensive, unmaintainable, and frustrating to management. We never bothered to produce an accurate conceptual model! If you don't rigorously describe an enterprise to begin with, why would anybody expect to be able to produce a relevant design and implementation that reflected the enterprise's reality or intent, or could be adapted over time to accommodate its changes?"
  • On the torturing, lonely journey you may find there are two places to rest, at least you can breathe a breath of relief or it seems two milestones you have to reach before the whole journey is finished:
    • a proposal of dynamic layer cake for data communication and correspondence of continuum for data semantics;
    • the other is taking the articulation of ontologies into consideration to find a way for multiple data sets interoperation.
    • Schemata and correspondences management using Telos, do you think the implementation of Telos, ConceptBase?
  • The well-known seemingly trivial example for illustrating the problem that when we need to connect heterogeneous autonomous systems with the purpose of interoperation, that propositions which well-behaved locally, i.e., within one system or system component, need not be static nor even consistent on a global system level: Schoenmaker's Conundrum, "A problem in knowledge acquisition," ACM SIGART Newsletters #95(1986). In which one witness only tells the judge "p" but keeps to himself that "not q", while a second witness independently only tells the judge "if p then q" but also keeps to herself that "not q". Each witness is consistent, but the judge is able to derive "q", supposedly thereby hanging a hapless victim.
  • To develop more detail about the correspondence between representation and the subject matter, let us suppose that the representation is the familiar decimal place-value notation. In this notation there are ten digit symbols, "0,","1," ... "9," which represent the numbers 0 through 9. Notice that we distinguish here between symbols, such as "5," which are part of the representation, and numbers, such as 5, which are being represented, by placing quotation marks around the symbols. The distinction can be brought out more clearly by recalling the Roman notation system, in which "V" is the symbol for 5, there is no single digit symbol for the number 2, there is a single digit symbol for the number 50, namely, "L," and so on. In decimal notation numbers larger that 9 are represented by concatenating the digit symbols into strings, such as "65," which is a string of length 2 with "5" in the first position and "6" in the second position. The assignment of a number to a symbolic string is determined systematically by the decimal place-value function, in which the contribution of each digit symbol to the assignment is determined jointly by its basic assignment and its position in the string. For example, knowing that the basic assignments of "6" and "5" are 6 and 5 and knowing the place-value function, one can determine that the assignment of "65" is 6x101 + 5x100, which equals 60+5, or 65. The decimal place-value function establishes a one-to-one correspondence, or mapping, between digit strings and numbers. Note that although the Roman system also uses strings of digit symbols to represent numbers, the mapping between strings and numbers cannot be defined as a place-value function.
  • A common attitude toward philosophy is that philosophers never answer question, but merely pose them. Scientists, in contrast, are in the business of delivering answers. Questions the answers to which elude science, questions that seem scientifically unanswerable, are often dismissed as "merely philosophical." Where philosophy is concerned, there are no settled truths: every opinion is as good as any other.
  • The principle of charity = When analysing and evaluating any argument, assume that the arguer intends to present the most convincing argument possible, while still ensuring that your interpretation of the argument agrees with the arguer's intent.
  • One of the usefulnesses the Semantic Web would provide is the accurate query ability in contrast to the keyword query used in today's Web such as Google search. It is doubtful that people will prefer an accurately meaningful query to the keyword query over Web. It should be a research topic for sociologists to do some in-depth studies to know whether the Semantic Web will be viable.